Difference between revisions of "Manuals/calci/CHOLESKYFACTORIZATION"

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==Examples==
 
==Examples==
1. CHOLESKYFACTORIZATION([[25, 15, -5],[15, 18, 0],[ -5, 0, 11]])
+
{| class="wikitable"
 +
|+Spreadsheet
 +
|-
 +
! !! A !! B !! C       
 +
|-
 +
! 1
 +
| 25 || 15 || -5  
 +
|-
 +
! 2
 +
| 15 || 18 || 0
 +
|-
 +
! 3
 +
| -5 || 0 || 11
 +
|}
 +
=CHOLESKYFACTORIZATION(A1:C3)
 +
 
 
{| class="wikitable"
 
{| class="wikitable"
 
|+Result
 
|+Result
Line 67: Line 82:
 
| 3.5355339059327373|| 4.415880433163924
 
| 3.5355339059327373|| 4.415880433163924
 
|}
 
|}
 
  
 
==See Also==
 
==See Also==

Revision as of 09:17, 4 September 2017

CHOLESKYFACTORIZATION(Matrix)


  • is the array of numeric elements

Description

  • This function gives the value of Cholesky factorization.
  • It is called Cholesky Decomposition or Cholesky Factorization.
  • In , is the set of values.
  • The Cholesky Factorization is only defined for symmetric or Hermitian positive definite matrices.
  • Every positive definite matrix A can be factored as =
 is lower triangular with positive diagonal elements
 is is the conjugate transpose value of 
  • Every Hermitian positive-definite matrix has a unique Cholesky decomposition.
  • Here , is set of values to find the factorization value.
  • Partition matrices in = is

Algorithm

  1. Determine and
  2. = =
  3. Compute from
  4. =
    • This is a Cholesky Factorization of order
*If the matrix A is Hermitian and positive semi-definite, then it still has a decomposition of the form A = LL^T if the diagonal entries of L are allowed to be zero.
*Also A can be written as LL^T for some invertible L, lower triangular or otherwise, then A is Hermitian and positive definite.

Examples

Spreadsheet
A B C
1 25 15 -5
2 15 18 0
3 -5 0 11

=CHOLESKYFACTORIZATION(A1:C3)

Result
5 0 0
3 3 0
-1 1 3

2. CHOLESKYFACTORIZATION([[8,14],[10,32]])

Result
2.8284271247461903 0
3.5355339059327373 4.415880433163924

See Also

References